#read data
Aprildata_with_nebhod = read_csv("./data/Aprildata_with_nebhod.csv") ## Parsed with column specification:
## cols(
## MODZCTA = col_double(),
## month = col_character(),
## date = col_double(),
## positive = col_double(),
## total = col_double(),
## zcta_cum_perc_pos = col_double(),
## newcases_apr_day = col_double(),
## neighborhood_name = col_character(),
## borough_group = col_character(),
## time = col_character()
## )May_data = read_csv("./data/May_data.csv")## Parsed with column specification:
## cols(
## modified_zcta = col_double(),
## month = col_character(),
## date = col_double(),
## positive = col_double(),
## total = col_double(),
## zcta_cum_perc_pos = col_double(),
## neighborhood_name = col_character(),
## borough_group = col_character(),
## covid_case_rate = col_logical(),
## pop_denominator = col_logical(),
## covid_death_count = col_logical(),
## covid_death_rate = col_logical(),
## percent_positive = col_logical(),
## newcases_day = col_double()
## )## Warning: 12319 parsing failures.
## row col expected actual file
## 3010 covid_case_rate 1/0/T/F/TRUE/FALSE 1421.72 './data/May_data.csv'
## 3010 pop_denominator 1/0/T/F/TRUE/FALSE 23563.03 './data/May_data.csv'
## 3010 covid_death_count 1/0/T/F/TRUE/FALSE 17 './data/May_data.csv'
## 3010 covid_death_rate 1/0/T/F/TRUE/FALSE 72.15 './data/May_data.csv'
## 3010 percent_positive 1/0/T/F/TRUE/FALSE 24.26 './data/May_data.csv'
## .... ................. .................. ........ .....................
## See problems(...) for more details.Junedata = read_csv("./data/Junedata.csv")## Warning: Missing column names filled in: 'X1' [1]## Parsed with column specification:
## cols(
## X1 = col_double(),
## zipcode = col_double(),
## neighborhood_name = col_character(),
## borough_group = col_character(),
## positive = col_double(),
## covid_case_rate = col_double(),
## pop_denominator = col_double(),
## covid_death_count = col_double(),
## covid_death_rate = col_double(),
## percent_positive = col_double(),
## day = col_character(),
## total_covid_tests = col_double(),
## newcases_june = col_double()
## )data_to_plot = Junedata %>% filter(day == "June30")
spdf = rgdal::readOGR("/Users/ziqizhou/Desktop/MSPH_1st_Year/P8105_Data_Science/Git/zipcode_covid-19/data/Geography-resources/MODZCTA_2010_WGS1984.geo.json")## OGR data source with driver: GeoJSON
## Source: "/Users/ziqizhou/Desktop/MSPH_1st_Year/P8105_Data_Science/Git/zipcode_covid-19/data/Geography-resources/MODZCTA_2010_WGS1984.geo.json", layer: "MODZCTA_2010_WGS1984.geo"
## with 178 features
## It has 2 fieldspopup_sb_newcases <- paste0("<b> MODZCTA: </b>", Junedata$zipcode,
"<br>",
"<b> NTA: </b>", Junedata$neighborhood_name,
"<br>",
"<b> Borough: </b>", Junedata$borough_group,
"<br>",
"<b> New Cases: </b>", Junedata$newcases_june)
popup_sb_cumulative <- paste0("<b> MODZCTA: </b>", Junedata$zipcode,
"<br>",
"<b> NTA: </b>", Junedata$neighborhood_name,
"<br>",
"<b> Borough: </b>", Junedata$borough_group,
"<br>",
"<b> Cumulative Cases: </b>", Junedata$positive)
popup_sb_pos_rate <- paste0("<b> MODZCTA: </b>", Junedata$zipcode,
"<br>",
"<b> NTA: </b>", Junedata$neighborhood_name,
"<br>",
"<b> Borough: </b>", Junedata$borough_group,
"<br>",
"<b> Case Rate: </b>", Junedata$covid_case_rate)
popup_sb_death <- paste0("<b> MODZCTA: </b>", Junedata$zipcode,
"<br>",
"<b> NTA: </b>", Junedata$neighborhood_name,
"<br>",
"<b> Borough: </b>", Junedata$borough_group,
"<br>",
"<b> Death Count: </b>", Junedata$covid_death_count)
popup_sb_death_rate <- paste0("<b> MODZCTA: </b>", Junedata$zipcode,
"<br>",
"<b> NTA: </b>", Junedata$neighborhood_name,
"<br>",
"<b> Borough: </b>", Junedata$borough_group,
"<br>",
"<b> Death Rate: </b>", Junedata$covid_death_rate)#draw a map for cumulative cases
data_to_plot = geo_join(spdf,data_to_plot,"MODZCTA","zipcode")
# Getting rid of rows with NA values
data_to_plot <- subset(data_to_plot, !is.na(positive))
pal_cum <- colorNumeric("Greens", domain=data_to_plot$positive)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
setView(lng = -73.99653, lat = 40.71181, zoom = 11) %>%
addPolygons(data = data_to_plot ,
fillColor = ~pal_cum(data_to_plot$positive),
fillOpacity = 0.7,
weight = 0.2,
smoothFactor = 0.2,
popup = ~popup_sb_cumulative) %>%
addLegend(pal = pal_cum,
values = data_to_plot$positive,
position = "bottomright",
title = "Cumulative Cases Count in June 30")data_to_plot <- subset(data_to_plot, !is.na(covid_case_rate))
pal_posr <- colorNumeric("Greens", domain=data_to_plot$covid_case_rate)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
setView(lng = -73.99653, lat = 40.71181, zoom = 11) %>%
addPolygons(data = data_to_plot ,
fillColor = ~pal_posr(data_to_plot$covid_case_rate),
fillOpacity = 0.7,
weight = 0.2,
smoothFactor = 0.2,
popup = ~popup_sb_pos_rate) %>%
addLegend(pal = pal_posr,
values = data_to_plot$covid_case_rate,
position = "bottomright",
title = "COVID-19 Cases Rate in June 30")data_to_plot <- subset(data_to_plot, !is.na(newcases_june))
pal_new <- colorNumeric("Greens", domain=data_to_plot$newcases_june)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
setView(lng = -73.99653, lat = 40.71181, zoom = 11) %>%
addPolygons(data = data_to_plot ,
fillColor = ~pal_new(data_to_plot$newcases_june),
fillOpacity = 0.7,
weight = 0.2,
smoothFactor = 0.2,
popup = ~popup_sb_newcases) %>%
addLegend(pal = pal_new,
values = data_to_plot$newcases_june,
position = "bottomright",
title = "New Cases Count in June 29")#draw a map for death cases
data_to_plot <- subset(data_to_plot, !is.na(covid_death_count))
pal_death <- colorNumeric("Greens", domain=data_to_plot$covid_death_count)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
setView(lng = -73.99653, lat = 40.71181, zoom = 11) %>%
addPolygons(data = data_to_plot ,
fillColor = ~pal_death(data_to_plot$covid_death_count),
fillOpacity = 0.7,
weight = 0.2,
smoothFactor = 0.2,
popup = ~popup_sb_death) %>%
addLegend(pal = pal_death,
values = data_to_plot$covid_death_count,
position = "bottomright",
title = "Death Count in June 30")#draw a map for death rate
data_to_plot <- subset(data_to_plot, !is.na(covid_death_rate))
pal_death_rate <- colorNumeric("Greens", domain=data_to_plot$covid_death_rate)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
setView(lng = -73.99653, lat = 40.71181, zoom = 11) %>%
addPolygons(data = data_to_plot ,
fillColor = ~pal_death_rate(data_to_plot$covid_death_rate),
fillOpacity = 0.7,
weight = 0.2,
smoothFactor = 0.2,
popup = ~popup_sb_death_rate) %>%
addLegend(pal = pal_death_rate,
values = data_to_plot$covid_death_rate,
position = "bottomright",
title = "Death Rate in June 30")